Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer
Despite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used...
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| Format: | Article |
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MDPI AG
2022-11-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/12/12/1947 |
| _version_ | 1797456848417193984 |
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| author | Chin-Chou Wang Wan-Jou Shen Gangga Anuraga Hoang Dang Khoa Ta Do Thi Minh Xuan Sih-Tong Chen Chiu-Fan Shen Jia-Zhen Jiang Zhengda Sun Chih-Yang Wang Wei-Jan Wang |
| author_facet | Chin-Chou Wang Wan-Jou Shen Gangga Anuraga Hoang Dang Khoa Ta Do Thi Minh Xuan Sih-Tong Chen Chiu-Fan Shen Jia-Zhen Jiang Zhengda Sun Chih-Yang Wang Wei-Jan Wang |
| author_sort | Chin-Chou Wang |
| collection | DOAJ |
| description | Despite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used as systematic approaches to explore differences in expressions of thousands of genes for both biological and genomic systems. Recently, using big data analyses in biomedicine research by integrating several high-throughput databases and tools, including The Cancer Genome Atlas (TCGA), cBioportal, Oncomine, and Kaplan–Meier plotter, is an important strategy to identify novel biomarkers for cancer therapy. Here, we used two different comprehensive bioinformatics analysis and revealed protein tyrosine phosphatase non-receptor type (PTPN) family genes, especially PTPN1 and PTPN22, were downregulated in lung cancer tissue in comparison with normal samples. The survival curves indicated that LUAD patients with high transcription levels of PTPN5 were significantly associated with a good prognosis. Meanwhile, Gene Ontology (GO) and MetaCore analyses indicated that co-expression of the PTPN1, PTPN5, and PTPN21 genes was significantly enriched in cancer development-related pathways, including GTPase activity, regulation of small GTPase-mediated signal transduction, response to mechanical stimuli, vasculogenesis, organ morphogenesis, regulation of stress fiber assembly, mitogen-activated protein kinase (MAPK) cascade, cell migration, and angiogenesis. Collectively, this study revealed that PTPN family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, which provide new targets for treating LUAD patients. |
| first_indexed | 2024-03-09T16:13:44Z |
| format | Article |
| id | doaj.art-3f2213f99b5540b684a8a213ff647c02 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-09T16:13:44Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-3f2213f99b5540b684a8a213ff647c022023-11-24T16:00:58ZengMDPI AGJournal of Personalized Medicine2075-44262022-11-011212194710.3390/jpm12121947Novel Potential Therapeutic Targets of PTPN Families for Lung CancerChin-Chou Wang0Wan-Jou Shen1Gangga Anuraga2Hoang Dang Khoa Ta3Do Thi Minh Xuan4Sih-Tong Chen5Chiu-Fan Shen6Jia-Zhen Jiang7Zhengda Sun8Chih-Yang Wang9Wei-Jan Wang10Divisions of Pulmonary & Critical Care Medicine, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, TaiwanDepartment of Biological Science and Technology, China Medical University, Taichung 40676, TaiwanGraduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanGraduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanGraduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanDepartment of Biological Science and Technology, China Medical University, Taichung 40676, TaiwanDivisions of Pulmonary & Critical Care Medicine, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, TaiwanEmergency Department, Huashan Hospital North, Fudan University, Shanghai 201508, ChinaKaiser Permanente, Northern California Regional Laboratories, The Permanente Medical Group, 1725 Eastshore Hwy, Berkeley, CA 94710, USAGraduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanDepartment of Biological Science and Technology, China Medical University, Taichung 40676, TaiwanDespite the treatment of lung adenocarcinoma (LUAD) having partially improved in recent years, LUAD patients still have poor prognosis rates. Therefore, it is especially important to explore effective biomarkers and exploit novel therapeutic developments. High-throughput technologies are widely used as systematic approaches to explore differences in expressions of thousands of genes for both biological and genomic systems. Recently, using big data analyses in biomedicine research by integrating several high-throughput databases and tools, including The Cancer Genome Atlas (TCGA), cBioportal, Oncomine, and Kaplan–Meier plotter, is an important strategy to identify novel biomarkers for cancer therapy. Here, we used two different comprehensive bioinformatics analysis and revealed protein tyrosine phosphatase non-receptor type (PTPN) family genes, especially PTPN1 and PTPN22, were downregulated in lung cancer tissue in comparison with normal samples. The survival curves indicated that LUAD patients with high transcription levels of PTPN5 were significantly associated with a good prognosis. Meanwhile, Gene Ontology (GO) and MetaCore analyses indicated that co-expression of the PTPN1, PTPN5, and PTPN21 genes was significantly enriched in cancer development-related pathways, including GTPase activity, regulation of small GTPase-mediated signal transduction, response to mechanical stimuli, vasculogenesis, organ morphogenesis, regulation of stress fiber assembly, mitogen-activated protein kinase (MAPK) cascade, cell migration, and angiogenesis. Collectively, this study revealed that PTPN family members are both significant prognostic biomarkers for lung cancer progression and promising clinical therapeutic targets, which provide new targets for treating LUAD patients.https://www.mdpi.com/2075-4426/12/12/1947PTPN family geneslung cancerprognosisbioinformaticsbig data analysis |
| spellingShingle | Chin-Chou Wang Wan-Jou Shen Gangga Anuraga Hoang Dang Khoa Ta Do Thi Minh Xuan Sih-Tong Chen Chiu-Fan Shen Jia-Zhen Jiang Zhengda Sun Chih-Yang Wang Wei-Jan Wang Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer Journal of Personalized Medicine PTPN family genes lung cancer prognosis bioinformatics big data analysis |
| title | Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer |
| title_full | Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer |
| title_fullStr | Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer |
| title_full_unstemmed | Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer |
| title_short | Novel Potential Therapeutic Targets of PTPN Families for Lung Cancer |
| title_sort | novel potential therapeutic targets of ptpn families for lung cancer |
| topic | PTPN family genes lung cancer prognosis bioinformatics big data analysis |
| url | https://www.mdpi.com/2075-4426/12/12/1947 |
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